docstr: This encoder handles arrays of numerical time series data by wrapping the numerical encoder with behavior specific to time series tasks.
  
  :param timesteps: length of forecasting horizon, as defined by TimeseriesSettings.window.
  :param is_target: whether this encoder corresponds to the target column.
  :param positive_domain: whether the column domain is expected to be positive numbers.
  :param grouped_by: what columns, if any, are considered to group the original column and yield multiple time series.
docstr_tok: ["This","encoder","handles","arrays","of","numerical","time","series","data","by","wrapping","the","numerical","encoder","with","behavior","specific","to","time","series","tasks",".",":","param","timesteps",":","length","of","forecasting","horizon",",","as","defined","by","TimeseriesSettings.window",".",":","param","is_target",":","whether","this","encoder","corresponds","to","the","target","column",".",":","param","positive_domain",":","whether","the","column","domain","is","expected","to","be","positive","numbers",".",":","param","grouped_by",":","what","columns",",","if","any",",","are","considered","to","group","the","original","column","and","yield","multiple","time","series","."]
code: def __init__(
      self,
      timesteps: int,
      is_target: bool = False,
      positive_domain: bool = False,
      grouped_by=None,
      nan=0,
  ):
      """
      This encoder handles arrays of numerical time series data by wrapping the numerical encoder with behavior specific to time series tasks.
  
      :param timesteps: length of forecasting horizon, as defined by TimeseriesSettings.window.
      :param is_target: whether this encoder corresponds to the target column.
      :param positive_domain: whether the column domain is expected to be positive numbers.
      :param grouped_by: what columns, if any, are considered to group the original column and yield multiple time series.
      """  # noqa
      super(TsArrayNumericEncoder, self).__init__(is_target=is_target)
      self.normalizers = None
      self.group_combinations = None
      self.dependencies = grouped_by
      self.data_window = timesteps
      self.positive_domain = positive_domain
      self.nan_value = nan
      self.sub_encoder = TsNumericEncoder(
          is_target=is_target,
          positive_domain=positive_domain,
          grouped_by=grouped_by,
      )
      self.output_size = self.data_window * self.sub_encoder.output_size
  
file_path: lightwood/lightwood/encoder/array/ts_num_array.py
imports: from typing import List, Dict, Iterable, Optional
  import torch
  from lightwood.encoder import BaseEncoder
  from lightwood.encoder.numeric import TsNumericEncoder
label_desc: Use image node_id 1 to create a new TsArrayNumericEncoder object from inherited base classes: BaseEncoder with example: obj = TsArrayNumericEncoder(timesteps, is_target, positive_domain, grouped_by, nan)